AI is upending not only the way people work, but also their relationship to work—their professional identity. AI is uniquely impacting white-collar workers in unprecedented ways.
In the past, automation technologies have focused on automating parts of the physical tasks that humans perform. The rise of robotics has done just that, displacing low-skilled workers from the manufacturing process of goods like cars. On the other hand, the development of software affects middle-skilled workers by automating more complex tasks. AI is now pursuing white-collar skills—decision-making and intelligence—skills that until recently we thought were unique to humans.
The new field of generative AI has eroded white-collar jobs even further than previous AI systems. That’s because, as Microsoft CEO Satya Nadella outlined in his recent company keynote address, there are two layers driving the capabilities of generative AI: First, advanced inference engines that can use Pre-train on general information and then retrain on company information. Concrete data that provides customized insights; Second, a natural language interface that makes English the “hottest new programming language.” The upshot is that generative AI can deliver complex insights, but also in an understandable way. This capability is similar to the work of senior employees, disrupting white-collar professional identities.
Proactively addressing these professional identity issues is critical for organizations, as employees who feel their professional identity is threatened by AI will be more resistant to AI adoption and less likely to use and derive value from AI. This ultimately hurts the entire company. Our research shows that organizations where employees see value from AI first-hand are nearly six times more likely to see significant financial benefit than organizations where employees don’t see the value in the technology.
There are many schools of thought about what constitutes an individual’s unique professional identity and how it evolves over time. According to self-determination theory, professional identity is made up of three key components: competence (the importance of the role and belief in one’s own expertise), autonomy (level of discretion in making decisions), and belonging (connectivity with the wider group connection, yielding meaning). To address AI’s impact on employees’ professional identity, executives need to address each of these three elements.
Redesigning characters to put humans ahead of artificial intelligence
When AI takes on tasks previously performed by humans, it has the potential to damage employees’ sense of competence. For example, AI can now outperform radiologists in diagnostic accuracy. As a result, many medical students forego potential careers in radiology because their sense of competence is diminished by AI excellence in the field. The rapid growth of generative AI in the workplace is having a similar impact on employees’ perceptions of competence in a growing number of industries.
What is meaningful work for humans in this new reality? To create a new sense of purpose, organizations need to identify which tasks humans are particularly suited to and separate them from tasks that AI excels at. Deploying AI to handle these diverse tasks frees up human workers to take on roles that have capabilities beyond AI, which allows human workers to add value in the presence of AI, enabling them to acquire new capabilities at work feel.
When H&M tapped artificial intelligence to make annual purchasing decisions about how much and what type of clothes to buy for its global markets, the retailer’s buying team first condemned the move, then resisted it. While the tedious task of purchasing itself, involving hundreds of thousands of hours of manual work, can now be automated through artificial intelligence, the feeling of being displaced affects how workers perceive themselves and their jobs, fundamentally altering their professional identities. The resistance of H&M buyers has hindered the adoption of artificial intelligence and may eliminate the economic benefits of the technology for the company.
To help overcome their opposition to the move, H&M helped employees find a new sense of purpose. The company redefined the roles of employees to emphasize what they do best. These employees no longer manually calculate discounts on declining products; they calculate discounts manually. Now, they work on complex new product launches and analyze customer behavior. To further solidify the changes, the company renamed teams to reflect the new roles, paving the way for employees to forge new career narratives.Inspired by these changes, H&M employees feel empowered, regain a sense of competence, and invest in the use of artificial intelligence
Making AI ‘challenging’ restores employee autonomy
Unlike previous automation advances, AI has a unique ability to make decisions, or at least provide guidance on which decisions should be made. This leaves employees feeling dependent on machines to make decisions, fundamentally threatening their autonomy. The increasing decision-making capabilities of generative AI will only intensify this threat, especially with the rise of autonomous agents such as AutoGPT and BabyAGI, which can not only make decisions, but independently plan, solve problems and execute entire tasks to achieve specific Target.
This violation of employee autonomy has several negative consequences. For example, increased autonomy can improve employee performance and retention while reducing employee fatigue, according to a recent study by IT research firm Gartner. So how can leaders restore a sense of autonomy to their employees?
First, leaders must ensure that AI implementations allow overriding privileges. This restores a sense of agency and creates a virtuous feedback loop that makes employees more likely to adopt AI first. For example, a well-known human bias is “algorithm aversion,” the distrust and rejection of AI, even if it is powerful, when it cannot perform to absolute perfection. Academic research has shown that giving participants the ability to modify AI output can overcome this aversion—regardless of the extent or frequency with which participants modify the output. Override permissions also play a key role, allowing trained experts to correct AI mistakes when the technology goes off track.
Second, leaders must emphasize to employees that the use of AI can increase employees’ sense of autonomy by reducing supervisor oversight. At Walgreens, for example, managers initially controlled how pharmacists filled prescriptions with strict guidelines designed to ensure patient satisfaction. With the adoption of AI comes a new system: AI will predict when pharmacy orders will be ready to reduce wait times for customers. This means fewer interventions are required from management, such as fulfilling guidance. In fact, in one instance, a manager called to congratulate pharmacists for reducing customer complaints and ultimately giving individual pharmacists more agency to run their businesses as they saw fit. This greatly increases the sense of autonomy for Walgreens pharmacists.
Rebuild a sense of belonging by cultivating new types of connections
AI can negatively impact an individual’s sense of belonging by reducing human interaction around AI-automated tasks. This has already happened in factories, where the few remaining employees mostly work in tandem with the machines but are isolated from each other to ensure quality control.
Generative AI, capable of lifelike chatbot conversations, is making this threat even more prevalent. Within companies, some human-to-human interactions have been replaced by chatbot interactions. Staying away from these small workplace interactions creates a big problem: It reduces employees’ sense of belonging, which hurts their well-being, which in turn hurts business performance. A 2019 survey by BetterUp found that a strong sense of belonging in the workplace leads to a 56% increase in job performance, a 50% reduction in employee turnover, and a 75% reduction in employee sick days.
One solution to employee isolation is to redesign the company’s workflow. For example, a U.S. bank’s call center created “squads,” or teams of operators, to support similar customers and leveraged AI-powered software to generate more opportunities for interaction—virtual channels, break synchronization, and tracking of common goals. team level. A year after the bank implemented the software, its call center reported a 23% increase in productivity and a 28% increase in employee retention. The role of these teams goes far beyond pure efficiency gains. Digital services company Oomph has seen impressive results: Team happiness, productivity and success have increased dramatically since the squad was created. Squads have improved Oomph’s culture, which has yielded tremendous benefits at both the employee and organizational levels.
There is no doubt that the emergence of artificial intelligence, especially generative artificial intelligence, is a technological revolution. However, as organizations hope to reap the full benefits of this technological revolution, they must now turn their attention to the human impact of this revolution. As AI continues to cement its place in the workplace, it poses unique challenges for employees and their professional identities. The key is to recognize the magnitude of this occupational identity threat and create an environment where humans can thrive alongside AI. Achieving this will require action not just from the top executives, but from managers at every level of the organization.
read other wealth Column by François Candelon.
François Candelon is a managing director and senior partner in the Paris office of Boston Consulting Group and global director of the BCG Henderson Institute (BHI).
Lisa Krayer is a Program Leader and BHI Ambassador in BCG’s Washington, DC office.
Saravanan Rajendran is a Program Leader and BHI Ambassador in BCG’s San Francisco office.
Some of the companies featured in this column are past or current BCG clients.